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ChatGPT has become very popular since the beginning of November 2022. Its increasing popularity has sparked numerous debates online on how it might transform businesses and living. Even the medical industry is gradually accepting this generative technology, but is it time to fully merge ChatGPT and healthcare? This article will discuss natural language processing models and other artificial intelligence-based tools through the lenses of physicians, patients, and corporations.
AI’s Expanding Role in Diagnosis, Treatment Support, and Clinical Workflows
A recent study by the National Library of Medicine highlighted the need for faster and more flexible healthcare. Doctors noticed that patients are taking more responsibility for their health. With the right tests and resources, doctors can better understand diseases. Can ChatGPT be a useful tool in this process? For now, it has the potential to identify trends in medical images such as X-rays, MRIs, and CT scans. Such a breakthrough enhances diagnosis and early treatments, which ensures improved patient outcomes.
ChatGPT will primarily reduce the burden of administrative activities on doctors, allowing them to be more focused on treating patients. According to a National Health Service poll, 44% of people who took part in the survey indicated that AI would improve disease prevention the most, while 43% were afraid that ‘AI will mostly threaten health care jobs and professional status.’
Nonetheless, AI does not always outperform human decision-making, especially in a profession guided by the integrity and compassion central to the Hippocratic Oath. Therefore, AI must work under rigid rules and regulated data to serve the goal of accuracy. A good example of this collaboration is when a doctor types some symptoms into the program, and the AI adds this data to the patient’s history. It can even recommend what treatments could be the most effective, but the doctor analyzes the data and makes the final decision. With time, the number of mistakes will diminish, and these systems will improve as they learn through interactions with doctors, making their decisions better.
How AI Tools Are Reshaping Medical Research and Clinical Practice
The National Library of Medicine considered two primary usages of ChatGPT: in healthcare settings and medical writing and research. The 118 articles they analyzed were applied so that they could analyze how ChatGPT can perform several essential functions in medical research. For starters, it helps in data collection, analysis, and interpretation. Generative language processing also aids scientific writing, medical decision-making, and medical education. All in all, AI-based programs simplify tasks such as collecting patient questionnaires, capturing interview content, and analyzing epidemiological information. Because it is so fast, ChatGPT can help investigators find important information, develop hypotheses, analyze findings, and shorten study schedules. But that is not all; it has been known to write texts, create drafts, brainstorm, suggest synonyms, edit, and proofread. Nevertheless, the quality and accuracy need human inspection.
Support, Skepticism, and the Human Connection
The Health Foundation commissioned a survey in June and July 2024 to understand how people and healthcare professionals feel about using AI in healthcare. The poll involved 7,201 non-staff members (aged 16 years or more) and 1,292 employees.
The population and employees mostly favor the application of AI in medical care. 54% of people across the UK and 76% of National Health Service workers are in favor of AI in patient care. There is even more support for utilizing AI to carry out administrative work, ranging from 61% and 81% of people who answered the question.
Many people still do not support AI. About 1 in 6 people in the general population and 1 in 10 National Health Service employees believe that AI could lower the quality of care. Furthermore, women are less likely to agree with the idea that ChatGPT can somehow raise the level of patient care. This underlines the necessity of reaching out to people and employees to understand their fears and concerns.
The first issue is the impact that AI may have on interpersonal relationships in health care. 53% of respondents believe that artificial intelligence will distance them from their caregivers. Almost two out of three National Health Service staff members (65%) think that AI will make them feel more disconnected from patients. Such findings indicate that technologies based on AI should not deteriorate, but rather enhance the human element of care.
About 30% of people believe a significant disadvantage is that healthcare workers might not verify natural language processing models’ outputs, leading to potential errors. However, in cases when humans are in charge of overseeing language processing programs, respondents claim they would be ready to accept “artificial” decision-making.
57% of the National Health Service personnel expect AI to be introduced as a reviewing tool in and of their jobs, but opinions vary among different occupational groups. Medical and dental staff tend to be more optimistic than clinical personnel, such as health care assistants and support workers. Since the integration of more virtual writing assistants is becoming familiar to healthcare workers, policymakers and leaders should address the diverse impacts of AI on different jobs, offering corresponding support.
Is Medicine Ready for AI? Benefits, Challenges, and Ethical Guardrails
Still, some reputable institutions think humanity is ready for AI. For instance, Harvard Medical School offers an eight-week online course, AI in Health Care: From Strategies to Implementation, focusing on developing and using AI solutions in healthcare. Keep in mind that this program does not provide academic credit or professional certifications from Harvard Medical School.
Key statistics they share on their website include:
AI could halve treatment costs for diagnoses (Harvard School for Public Health).
It might enhance health outcomes by 40% (Harvard School of Public Health).
The AI healthcare market may reach $187.9 billion by 2030 (Statista).
Bear in mind that the National Library of Medicine’s review is not comprehensive due to limited studies on the model’s use in medical research and care. It only focuses on this specific AI language model and does not include terms related to the OpenAI language model or GPT-4. Their analysis excluded articles related to medical education because it does not cover potential applications and limitations in that area. The study did not compare this generative AI tool with other AI-powered technologies, which could have offered a broader perspective.
The bottom line is that although ChatGPT can generate content, it lacks the innovation and critical thinking required for medical practice. Human oversight remains crucial, as computer-generated text may appear authoritative yet be incorrect. When incorporating AI-generated work in articles, authors should carefully evaluate the output, follow the relevant journal guidelines, and indicate that ultimate authorship responsibility rests with the human writer.
Conclusion
People tend to overestimate new technologies’ short-term impact and underestimate their long-term consequences. At the moment, natural language processing models are not supposed to substitute healthcare professionals. Instead, its purpose is to facilitate their practice and improve patient outcomes and general health.
ChatGPT can help doctors with diagnosis, treatment planning, and evidence-based decisions if it uses protective measures and unbiased training data. Eventually, personal health tracking will help enhance patient experiences in developed regions and facilitate people’s access to healthcare in less developed areas. Effective risk assessment and management should guide how professionals use this technology.
The number of people understanding the benefits of artificial intelligence in healthcare is increasing, and organizations are investing in emerging technologies to optimize community health and well-being. With the improvement of tools such as ChatGPT’s capabilities, it is natural to assume that they will be applied to healthcare systems more often.
